@ironarachne/words

A comprehensive TypeScript/JavaScript library for procedural natural language generation, string manipulation, and grammatical inflection. Originally built to provide utility functions for producing natural-sounding English from component parts, it's perfect for text generators, game development, and formatting data seamlessly.

Full documentation is available at words.ironarachne.com/docs.

Installation

npm install @ironarachne/words

Features

The library is organized into specialized domains for all your procedural text needs:

🔤 Casing

Easily change string formats for code, IDs, or display.

• capitalize, uncapitalize, title (Title Case)
• camelCase, snakeCase, kebabCase, swapCase

📚 Grammar

Helpers for assembling dynamic sentences to keep your procedural text grammatically correct.

• Articles & Pronouns: Generate the correct article (a/an) or pronoun based on gender and context.
• Quantification: quantify(2, "apple") -> "2 apples"
• Verbs & Copulas: isAre(count), hasHave(count), wasWere(count) to match plurals automatically.
• Possessives: Properly format nouns (e.g., possessive("James") -> "James'", possessive("dog") -> "dog's").

🔄 Inflection

Robust rules and an expansive irregular dictionary (e.g., radius/radii, goose/geese, deer).

• pluralize(word: string)
• singularize(word: string)
• detectPlural(word: string)

🔢 Numbers

Format numbers as text or traditional numeric formats.

• getOrdinal(1) -> "1st"
• ordinalWord(1) -> "first"
• numberToWords(21) -> "twenty-one"
• romanize(4) -> "IV"

📝 Text Utilities

Create clean paragraphs, phrases, and text elements.

• Sentence Building: buildSentence(parts) automatically capitalizes and fixes terminal punctuation.
• Lists: arrayToPhrase(["apple", "banana"], "or") -> "apple or banana"
• Punctuation: fixPunctuation(text) fixes double-spaces, space-before-comma, and duplicate punctuation.
• Formatting: slugify, truncateWords, squish, stripPunctuation
• Metrics: wordCount, readingTime

Example Usage

Building grammatically accurate procedural sentences is simple:

import { quantify, isAre, arrayToPhrase, buildSentence } from "@ironarachne/words";

const enemyCount = 3;
const enemyType = "goblin";
const loot = ["gold coin", "rusty dagger"];

// "3 goblins"
const enemies = quantify(enemyCount, enemyType); 

// "are"
const copula = isAre(enemyCount); 

// "gold coin and rusty dagger"
const lootPhrase = arrayToPhrase(loot); 

const parts = [
  "there", copula, enemies, "guarding the", lootPhrase
];

// Returns: "There are 3 goblins guarding the gold coin and rusty dagger."
const text = buildSentence(parts); 
console.log(text);

Contributing and Setup

This project uses TypeScript, Vitest for testing, and Biome for formatting.

# Install dependencies
npm install

# Run the test suite
npm run test

# Build the project
npm run build

# Re-generate the TypeDoc documentation
npm run docs

License

MIT License.